Fuel economy predictions for heavy‐duty vehicles and quasi‐dimensional DI diesel engine numerical modeling

dc.contributor.advisorMatthews, Ronald D.
dc.contributor.advisorHall, Matthew John
dc.contributor.committeeMemberEllzey, Janet L.
dc.contributor.committeeMemberEzekoye, Ofodike A.
dc.contributor.committeeMemberBiros, George
dc.contributor.committeeMemberRoberts, Charles E.
dc.creatorAtes, Murat, 1982-
dc.creator.orcid0000-0003-1322-3556
dc.date.accessioned2018-09-11T19:54:08Z
dc.date.available2018-09-11T19:54:08Z
dc.date.created2016-05
dc.date.issued2016-05
dc.date.submittedMay 2016
dc.date.updated2018-09-11T19:54:09Z
dc.description.abstractA research team developed the University of Texas Fuel Economy Model to estimate the fuel consumption of both light-duty and heavy-duty vehicles operated on Texas roads. One of the objectives of the model was to be as flexible as possible in order to be capable of simulating a variety of vehicles, payloads, and traffic conditions. For heavy-duty vehicles, there are no prescribed driving cycles, there are no coastdown coefficients available from the EPA, and we relied on experimental brake specific fuel consumption maps for a few heavy-duty diesel engines. Heavy-duty vehicle drive cycles highly depend upon the vehicle load, the grade of the road, the engine size, and the traffic conditions. In order to capture real driving conditions 54 drive cycles with three different Class 8 trucks, three weight configurations, three traffic congestion levels, and two drivers are collected. Drive cycles obtained in this research include road grade and vehicle speed data with time. Due to the lack of data from EPA for calculating the road load force for heavy-duty vehicles, coastdown tests were performed. To generate generic fuel maps for the fuel economy model, a direct injection quasi-dimensional diesel engine model was developed based on in-cylinder images available in the literature. Sandia National Laboratory researchers obtained various images describing diesel spray evolution, spray mixing, premixed combustion, mixing controlled combustion, soot formation, and NOx formation via imaging technologies. Dec combined all of the available images to develop a conceptual diesel combustion model to describe diesel combustion from the start of injection up to the quasi-steady form of the jet. The end of injection behavior was left undescribed in this conceptual model because no clear image was available due to the chaotic behavior of diesel combustion. A conceptual end-of-injection diesel combustion behavior model was proposed to capture diesel combustion in its life span. A full-cycle quasi-dimensional direct injection diesel engine model was developed that represents the physical models, utilizing the conceptual model developed from imaging experiments and available experiment-based spray models, of the in-cylinder processes. The compression, expansion, and gas exchange stages are modeled via zero-dimensional single zone calculations. A full cycle simulation is necessary in order to capture the initial conditions of the closed section of the cycle and predict the brake specific fuel consumption accurately.
dc.description.departmentMechanical Engineering
dc.format.mimetypeapplication/pdf
dc.identifierdoi:10.15781/T29Z90X1H
dc.identifier.urihttp://hdl.handle.net/2152/68397
dc.language.isoen
dc.subjectQuasi-dimensional
dc.subjectDiesel
dc.subjectEngine
dc.subjectHeavy-duty
dc.subjectDirect injection
dc.subjectNumerical
dc.subjectModeling
dc.subjectCombustion
dc.subjectCoastdown
dc.subjectDrive cycle
dc.subjectFuel economy
dc.subjectMathematical
dc.subjectVehicle
dc.subjectSimulation
dc.subjectClass 8
dc.titleFuel economy predictions for heavy‐duty vehicles and quasi‐dimensional DI diesel engine numerical modeling
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentMechanical Engineering
thesis.degree.disciplineMechanical Engineering
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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